4.7 Article

Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2016.10.004

关键词

Green supplier selection; Multiple criteria decision analysis; PROMETHEE; Compromise ranking; Robustness analysis; Food industry

资金

  1. Polish Ministry of Science and Higher Education under the Iuventus Plus program [IP2015 029674 - 0296/IP2/2016/74]

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The food sector has a prodigious focus and is constantly gaining in importance in today's global economic marketplace. Due to an increasing global population, society faces a greater challenge for sustainable food production, quality, distribution, and food safety in the food supply chain. Adopting green supply chain management (GSCM) elements is essential for utilizing the food supply chain in an environmentally benign way. As a solution to the above challenge, the economic and green characteristics for supplier selection in green purchasing are studied in this paper. For an organization, the evaluation and selection of the green supplier is a vital issue due to several tangible and intangible criteria involved. Accordingly, we apply multiple criteria decision aiding techniques. We propose a hybrid approach that combines the revised Simos procedure, PROMETHEE methods, algorithms for constructing a group compromise ranking, and robustness analysis. At first, the revised Simos procedure is used to derive the criteria weights. Next, the PROMETHEE method is applied to rank the suppliers according to each Decision Maker's (DM's) preferences. Then, the compromise ranking is constructed to minimize the distance of the individual's rankings from the solution adopted by the whole group. For this purpose, we introduce and apply some original procedures based on Binary Linear Programming. Finally, the results are validated against the outcomes of robustness analysis. The applicability and efficiency of the proposed approach is endorsed with a case study in an Indian food industry. (C) 2016 Elsevier Ltd. All rights reserved.

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